We’ve got another exciting in-person edition this month at the AWS.
Schedule:
5pm: doors open
5.30pm: announcements and welcome
5.40pm: 1st Talk
6.10pm: 2nd Talk
6.40pm: Networking
7.10pm: doors close
Speakers:
? Fabio Ramos, Data Enginner @ Cevo Australia
Talk: Using Apache Iceberg in your modern data architecture
Talk Summary: I will discuss Apache Iceberg and the benefits it provides in managing large amounts of data. I will also cover how Apache Iceberg can be part of your modern data architecture by bringing a range of capabilities to your data lake, including ACID transactions, schema evolution, time travel, and incremental processing. If time permitting a quick demo on Spark streaming using AWS Glue and Kafka, otherwise I can just cover it over a presentation.
Speaker Bio: I have worked in a range of industries including education, property management, accounting, and auditing. As a cloud consultant, I’ve interacted with many stakeholders at various industry levels, ranging from startups, government agencies and enterprises. This has helped me to build an appreciation for learning and adapting to new environments, to develop an ability to work with different teams, and to interact with multiple stakeholders with different technical skills and different businesses objectives.
? Emil Pastor, Solution Architect Manager @ Neo4j
Talk: Connected Data in the Age of AI/ML using Graph Database and Data Science
Talk Summary: As AI/ML usage expands, businesses face significant challenges in making the most of their data. To address this, graph databases and data science are becoming increasingly valuable. This session will explore how connected data can unleash the power of AI/ML and highlight the crucial role that graph databases and data science play in the process.
The session will begin with an overview of graph databases, including their fundamental concepts, benefits for storing and querying connected data, and how graph data science can enhance AI/ML applications. We will then dive into the unique insights from analysing data as a graph.
Additionally, we will examine the latest graph data science tools and techniques, including graph algorithms, graph embeddings, deep learning methods for graph data and integration with Generative AI. We will explore how graph data science techniques solve complex problems like fraud detection, recommendation systems, and network analysis.
At the end of the session, attendees will understand how graph databases can unlock the potential of AI/ML.
Speaker Bio: Emil Pastor is a Solution Architect at Neo4j based in Sydney. He has been a data and AI professional, enabling organizations in various industries through strategy, architecture, use case delivery, and capability building to support stakeholders and client data professionals in leveraging their data assets. Prior to working at Neo4j, he worked as an Architect and Consultant for organizations like Microsoft, McKinsey & Company (QuantumBlack), EY, and Teradata.
Remember to bring along some great questions!
